Josh Dillon, Last Revised January 2022
This notebook examines an individual antenna's performance over a whole season. This notebook parses information from each nightly rtp_summarynotebook (as saved to .csvs) and builds a table describing antenna performance. It also reproduces per-antenna plots from each auto_metrics notebook pertinent to the specific antenna.
import os
from IPython.display import display, HTML
display(HTML("<style>.container { width:100% !important; }</style>"))
# If you want to run this notebook locally, copy the output of the next cell into the next line of this cell.
# antenna = "004"
# csv_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/_rtp_summary_'
# auto_metrics_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/auto_metrics_inspect'
# os.environ["ANTENNA"] = antenna
# os.environ["CSV_FOLDER"] = csv_folder
# os.environ["AUTO_METRICS_FOLDER"] = auto_metrics_folder
# Use environment variables to figure out path to the csvs and auto_metrics
antenna = str(int(os.environ["ANTENNA"]))
csv_folder = os.environ["CSV_FOLDER"]
auto_metrics_folder = os.environ["AUTO_METRICS_FOLDER"]
print(f'antenna = "{antenna}"')
print(f'csv_folder = "{csv_folder}"')
print(f'auto_metrics_folder = "{auto_metrics_folder}"')
antenna = "182" csv_folder = "/home/obs/src/H6C_Notebooks/_rtp_summary_" auto_metrics_folder = "/home/obs/src/H6C_Notebooks/auto_metrics_inspect"
display(HTML(f'<h1 style=font-size:50px><u>Antenna {antenna} Report</u><p></p></h1>'))
import numpy as np
import pandas as pd
pd.set_option('display.max_rows', 1000)
import glob
import re
from hera_notebook_templates.utils import status_colors, Antenna
# load csvs and auto_metrics htmls in reverse chronological order
csvs = sorted(glob.glob(os.path.join(csv_folder, 'rtp_summary_table*.csv')))[::-1]
print(f'Found {len(csvs)} csvs in {csv_folder}')
auto_metric_htmls = sorted(glob.glob(auto_metrics_folder + '/auto_metrics_inspect_*.html'))[::-1]
print(f'Found {len(auto_metric_htmls)} auto_metrics notebooks in {auto_metrics_folder}')
Found 34 csvs in /home/obs/src/H6C_Notebooks/_rtp_summary_ Found 32 auto_metrics notebooks in /home/obs/src/H6C_Notebooks/auto_metrics_inspect
# Per-season options
mean_round_modz_cut = 4
dead_cut = 0.4
crossed_cut = 0.0
def jd_to_summary_url(jd):
return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H6C_Notebooks/blob/main/_rtp_summary_/rtp_summary_{jd}.html'
def jd_to_auto_metrics_url(jd):
return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H6C_Notebooks/blob/main/auto_metrics_inspect/auto_metrics_inspect_{jd}.html'
this_antenna = None
jds = []
# parse information about antennas and nodes
for csv in csvs:
df = pd.read_csv(csv)
for n in range(len(df)):
# Add this day to the antenna
row = df.loc[n]
if isinstance(row['Ant'], str) and '<a href' in row['Ant']:
antnum = int(row['Ant'].split('</a>')[0].split('>')[-1]) # it's a link, extract antnum
else:
antnum = int(row['Ant'])
if antnum != int(antenna):
continue
if np.issubdtype(type(row['Node']), np.integer):
row['Node'] = str(row['Node'])
if type(row['Node']) == str and row['Node'].isnumeric():
row['Node'] = 'N' + ('0' if len(row['Node']) == 1 else '') + row['Node']
if this_antenna is None:
this_antenna = Antenna(row['Ant'], row['Node'])
jd = [int(s) for s in re.split('_|\.', csv) if s.isdigit()][-1]
jds.append(jd)
this_antenna.add_day(jd, row)
break
# build dataframe
to_show = {'JDs': [f'<a href="{jd_to_summary_url(jd)}" target="_blank">{jd}</a>' for jd in jds]}
to_show['A Priori Status'] = [this_antenna.statuses[jd] for jd in jds]
df = pd.DataFrame(to_show)
# create bar chart columns for flagging percentages:
bar_cols = {}
bar_cols['Auto Metrics Flags'] = [this_antenna.auto_flags[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jee)'] = [this_antenna.dead_flags_Jee[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jnn)'] = [this_antenna.dead_flags_Jnn[jd] for jd in jds]
bar_cols['Crossed Fraction in Ant Metrics'] = [this_antenna.crossed_flags[jd] for jd in jds]
bar_cols['Flag Fraction Before Redcal'] = [this_antenna.flags_before_redcal[jd] for jd in jds]
bar_cols['Flagged By Redcal chi^2 Fraction'] = [this_antenna.redcal_flags[jd] for jd in jds]
for col in bar_cols:
df[col] = bar_cols[col]
z_score_cols = {}
z_score_cols['ee Shape Modified Z-Score'] = [this_antenna.ee_shape_zs[jd] for jd in jds]
z_score_cols['nn Shape Modified Z-Score'] = [this_antenna.nn_shape_zs[jd] for jd in jds]
z_score_cols['ee Power Modified Z-Score'] = [this_antenna.ee_power_zs[jd] for jd in jds]
z_score_cols['nn Power Modified Z-Score'] = [this_antenna.nn_power_zs[jd] for jd in jds]
z_score_cols['ee Temporal Variability Modified Z-Score'] = [this_antenna.ee_temp_var_zs[jd] for jd in jds]
z_score_cols['nn Temporal Variability Modified Z-Score'] = [this_antenna.nn_temp_var_zs[jd] for jd in jds]
z_score_cols['ee Temporal Discontinuties Modified Z-Score'] = [this_antenna.ee_temp_discon_zs[jd] for jd in jds]
z_score_cols['nn Temporal Discontinuties Modified Z-Score'] = [this_antenna.nn_temp_discon_zs[jd] for jd in jds]
for col in z_score_cols:
df[col] = z_score_cols[col]
ant_metrics_cols = {}
ant_metrics_cols['Average Dead Ant Metric (Jee)'] = [this_antenna.Jee_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Dead Ant Metric (Jnn)'] = [this_antenna.Jnn_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Crossed Ant Metric'] = [this_antenna.crossed_metrics[jd] for jd in jds]
for col in ant_metrics_cols:
df[col] = ant_metrics_cols[col]
redcal_cols = {}
redcal_cols['Median chi^2 Per Antenna (Jee)'] = [this_antenna.Jee_chisqs[jd] for jd in jds]
redcal_cols['Median chi^2 Per Antenna (Jnn)'] = [this_antenna.Jnn_chisqs[jd] for jd in jds]
for col in redcal_cols:
df[col] = redcal_cols[col]
# style dataframe
table = df.style.hide_index()\
.applymap(lambda val: f'background-color: {status_colors[val]}' if val in status_colors else '', subset=['A Priori Status']) \
.background_gradient(cmap='viridis', vmax=mean_round_modz_cut * 3, vmin=0, axis=None, subset=list(z_score_cols.keys())) \
.background_gradient(cmap='bwr_r', vmin=dead_cut-.25, vmax=dead_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
.background_gradient(cmap='bwr_r', vmin=crossed_cut-.25, vmax=crossed_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
.background_gradient(cmap='plasma', vmax=4, vmin=1, axis=None, subset=list(redcal_cols.keys())) \
.applymap(lambda val: 'font-weight: bold' if val < dead_cut else '', subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
.applymap(lambda val: 'font-weight: bold' if val < crossed_cut else '', subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
.applymap(lambda val: 'font-weight: bold' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
.applymap(lambda val: 'color: red' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
.bar(subset=list(bar_cols.keys()), vmin=0, vmax=1) \
.format({col: '{:,.4f}'.format for col in z_score_cols}) \
.format({col: '{:,.4f}'.format for col in ant_metrics_cols}) \
.format('{:,.2%}', na_rep='-', subset=list(bar_cols.keys())) \
.set_table_styles([dict(selector="th",props=[('max-width', f'70pt')])])
This table reproduces each night's row for this antenna from the RTP Summary notebooks. For more info on the columns, see those notebooks, linked in the JD column.
display(HTML(f'<h2>Antenna {antenna}, Node {this_antenna.node}:</h2>'))
HTML(table.render(render_links=True, escape=False))
| JDs | A Priori Status | Auto Metrics Flags | Dead Fraction in Ant Metrics (Jee) | Dead Fraction in Ant Metrics (Jnn) | Crossed Fraction in Ant Metrics | Flag Fraction Before Redcal | Flagged By Redcal chi^2 Fraction | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | Average Dead Ant Metric (Jee) | Average Dead Ant Metric (Jnn) | Average Crossed Ant Metric | Median chi^2 Per Antenna (Jee) | Median chi^2 Per Antenna (Jnn) |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 2459849 | RF_maintenance | 100.00% | 0.00% | 100.00% | 0.00% | 100.00% | 0.00% | 3.855383 | 16.829936 | 37.831189 | 48.129627 | 1.498572 | 12.803980 | -2.711034 | 6.522558 | 0.7601 | 0.0680 | 0.5303 | 4.322743 | 1.365803 |
| 2459848 | RF_maintenance | 100.00% | 0.00% | 100.00% | 0.00% | 100.00% | 0.00% | 3.889377 | 14.998078 | 27.484441 | 31.305886 | 4.939860 | 21.737770 | -2.529562 | 4.193983 | 0.7402 | 0.0612 | 0.5305 | 3.258824 | 1.306613 |
| 2459847 | RF_maintenance | 100.00% | 0.00% | 100.00% | 0.00% | 100.00% | 0.00% | 3.286780 | 17.393825 | 26.151865 | 29.496350 | 7.778157 | 28.421879 | -1.048543 | 1.446354 | 0.7453 | 0.0430 | 0.5632 | 3.405763 | 1.343730 |
| 2459845 | RF_maintenance | 100.00% | 0.00% | 100.00% | 0.00% | 100.00% | 0.00% | 6.067371 | 19.961318 | 36.028998 | 41.047376 | 3.632353 | 16.470240 | -1.321810 | 2.019811 | 0.7296 | 0.0655 | 0.5879 | 7.814439 | 1.240979 |
| 2459844 | RF_maintenance | 100.00% | 0.00% | 100.00% | 0.00% | - | - | 41.298317 | 14.889959 | 171.537879 | 6.655057 | 91.163273 | 4.623611 | -2.445624 | 12.817141 | 0.8781 | 0.0366 | 0.4407 | nan | nan |
| 2459843 | RF_maintenance | 100.00% | 0.00% | 100.00% | 0.00% | 100.00% | 0.00% | 6.396738 | 19.941698 | 16.479589 | 20.305090 | 69.240909 | 71.007687 | -2.747641 | 2.601149 | 0.7460 | 0.0546 | 0.5864 | 5.437756 | 1.514515 |
| 2459842 | RF_maintenance | 100.00% | 0.00% | 100.00% | 0.00% | 100.00% | 0.00% | 0.562101 | 13.669732 | -0.885641 | 9.914313 | -2.683787 | -0.565022 | -1.602318 | 1.497989 | 0.7518 | 0.0508 | 0.5426 | 3.722610 | 1.501294 |
| 2459841 | RF_maintenance | 100.00% | 0.00% | 100.00% | 0.00% | - | - | 39.517404 | 15.215610 | 108.411565 | 4.592166 | 123.396389 | 8.225369 | 0.423623 | 8.847037 | 0.6861 | 0.0344 | 0.3461 | nan | nan |
| 2459839 | RF_maintenance | 100.00% | - | - | - | - | - | -0.483160 | -0.335713 | -1.234349 | -1.200311 | 3.168218 | 0.625387 | 11.535360 | 7.750606 | nan | nan | nan | nan | nan |
| 2459838 | RF_maintenance | 100.00% | 0.00% | 100.00% | 0.00% | 100.00% | 0.00% | 4.246101 | 20.880372 | 19.636755 | 23.549325 | 7.799046 | 28.599642 | -2.616841 | 2.304017 | 0.7620 | 0.0590 | 0.4760 | 5.636552 | 1.668640 |
| 2459836 | RF_maintenance | - | 0.00% | 0.00% | 0.00% | - | - | nan | nan | nan | nan | nan | nan | nan | nan | 0.7008 | 0.5330 | 0.4543 | nan | nan |
| 2459835 | RF_maintenance | 100.00% | 0.00% | 0.00% | 0.00% | - | - | 4.922677 | 4.954974 | 11.826375 | 0.705760 | 13.980431 | 69.797707 | -6.498965 | 72.737726 | 0.7819 | 0.4422 | 0.6059 | nan | nan |
| 2459833 | RF_maintenance | 100.00% | 0.00% | 34.95% | 0.00% | - | - | 15.780982 | 16.255146 | 51.038025 | 7.294666 | 113.751834 | 256.239672 | -0.754341 | 146.009039 | 0.7942 | 0.4085 | 0.6157 | nan | nan |
| 2459832 | RF_maintenance | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | 11.108815 | 8.303147 | 16.172813 | 14.614133 | 8.018944 | 0.176445 | -1.288315 | 21.452844 | 0.8043 | 0.4709 | 0.6045 | 3.167879 | 2.388502 |
| 2459831 | RF_maintenance | 100.00% | 100.00% | 100.00% | 0.00% | - | - | -0.174527 | -0.315835 | -1.036342 | -1.123362 | 3.367159 | 2.358612 | 6.690637 | 5.906790 | 0.0288 | 0.0265 | 0.0014 | nan | nan |
| 2459830 | RF_maintenance | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | 12.656442 | 7.717757 | 21.461123 | 21.041305 | 25.592522 | 5.401337 | -3.810343 | 40.986779 | 0.8002 | 0.4837 | 0.5842 | 5.101394 | 3.428949 |
| 2459829 | RF_maintenance | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | 9.732104 | 11.121478 | 21.218625 | 19.006246 | 16.754160 | 6.986638 | -5.444980 | 62.718553 | 0.7614 | 0.5912 | 0.4556 | 8.696794 | 6.049350 |
| 2459828 | RF_maintenance | 100.00% | 0.00% | 38.17% | 0.00% | 100.00% | 0.00% | 11.438031 | 5.858220 | 16.299139 | 17.982697 | 25.060113 | 125.565569 | -3.737757 | 219.170447 | 0.7944 | 0.4114 | 0.5683 | 0.000000 | 0.000000 |
| 2459827 | RF_maintenance | 100.00% | 0.00% | 22.02% | 0.00% | 100.00% | 0.00% | 8.050530 | 7.483698 | 26.739471 | 17.042145 | 14.881995 | 118.801985 | -1.551207 | 1.147623 | 0.7656 | 0.5962 | 0.4449 | 0.000000 | 0.000000 |
| 2459826 | RF_maintenance | 100.00% | 0.00% | 86.56% | 0.00% | 100.00% | 0.00% | 11.438567 | 18.412693 | 22.020084 | 36.067249 | 33.308063 | 33.218514 | -1.718336 | 11.530607 | 0.7913 | 0.3350 | 0.5735 | 0.000000 | 0.000000 |
| 2459825 | RF_maintenance | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | 11.996922 | 2.553797 | 16.956193 | 7.642397 | 18.667460 | 3.760572 | -0.877808 | 4.617942 | 0.7917 | 0.5874 | 0.5291 | 7.738032 | 6.047356 |
| 2459824 | RF_maintenance | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | 5.784974 | 1.666256 | 23.274730 | 7.098508 | 4.125275 | 7.511980 | -2.327407 | 36.311558 | 0.7395 | 0.7349 | 0.3760 | 8.326854 | 9.652617 |
| 2459823 | RF_maintenance | 100.00% | 0.00% | 100.00% | 0.00% | 100.00% | 0.00% | 15.421866 | 26.135180 | 18.755413 | 47.253742 | 24.220842 | 33.503137 | 10.591726 | 30.632902 | 0.7690 | 0.1316 | 0.4834 | 53.462581 | 5.233170 |
| 2459822 | RF_maintenance | 100.00% | 0.00% | 94.62% | 0.00% | 100.00% | 0.00% | 13.963081 | 27.434809 | 20.554135 | 43.474758 | 21.769330 | 27.984314 | -0.644091 | 0.967505 | 0.7914 | 0.1717 | 0.5521 | 5.352238 | 1.854803 |
| 2459821 | RF_maintenance | 100.00% | 0.00% | 26.88% | 0.00% | 100.00% | 0.00% | 15.752882 | 6.965426 | 20.320151 | 5.563514 | 18.180795 | 134.855845 | -1.699521 | 5.069013 | 0.7796 | 0.4693 | 0.5396 | 5.166188 | 3.515158 |
| 2459820 | RF_maintenance | 100.00% | 0.00% | 44.15% | 0.00% | 100.00% | 0.00% | 9.829794 | 15.556082 | 24.174927 | 31.286431 | 43.189761 | 19.395903 | -2.730088 | 40.627750 | 0.7732 | 0.4036 | 0.5044 | 5.127231 | 2.729458 |
| 2459817 | RF_maintenance | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | 15.682966 | 3.189414 | 16.826495 | 22.675547 | 25.854713 | 81.386069 | -0.379603 | 12.062639 | 0.7847 | 0.6080 | 0.5161 | 3.404875 | 2.659579 |
| 2459816 | RF_maintenance | 100.00% | 0.00% | 88.21% | 0.00% | 100.00% | 0.00% | 10.207241 | 19.580018 | 24.404789 | 42.743077 | 33.911830 | 39.422087 | -4.549940 | 8.226924 | 0.8371 | 0.2311 | 0.6551 | 3.798290 | 1.652686 |
| 2459815 | RF_maintenance | 100.00% | 0.00% | 65.05% | 0.00% | 100.00% | 0.00% | 14.701544 | 21.257362 | 19.086652 | 45.458950 | 33.629448 | 39.355068 | 2.277924 | 10.472590 | 0.7790 | 0.3516 | 0.5753 | 4.090111 | 1.742145 |
| 2459814 | RF_maintenance | 0.00% | - | - | - | - | - | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan |
| 2459813 | RF_maintenance | 100.00% | 100.00% | 100.00% | 0.00% | 100.00% | 0.00% | nan | nan | inf | inf | nan | nan | nan | nan | nan | nan | nan | 0.000000 | 0.000000 |
auto_metrics notebooks.¶htmls_to_display = []
for am_html in auto_metric_htmls:
html_to_display = ''
# read html into a list of lines
with open(am_html) as f:
lines = f.readlines()
# find section with this antenna's metric plots and add to html_to_display
jd = [int(s) for s in re.split('_|\.', am_html) if s.isdigit()][-1]
try:
section_start_line = lines.index(f'<h2>Antenna {antenna}: {jd}</h2>\n')
except ValueError:
continue
html_to_display += lines[section_start_line].replace(str(jd), f'<a href="{jd_to_auto_metrics_url(jd)}" target="_blank">{jd}</a>')
for line in lines[section_start_line + 1:]:
html_to_display += line
if '<hr' in line:
htmls_to_display.append(html_to_display)
break
These figures are reproduced from auto_metrics notebooks. For more info on the specific plots and metrics, see those notebooks (linked at the JD). The most recent 100 days (at most) are shown.
for i, html_to_display in enumerate(htmls_to_display):
if i == 100:
break
display(HTML(html_to_display))
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 182 | N13 | RF_maintenance | nn Power | 48.129627 | 3.855383 | 16.829936 | 37.831189 | 48.129627 | 1.498572 | 12.803980 | -2.711034 | 6.522558 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 182 | N13 | RF_maintenance | nn Power | 31.305886 | 14.998078 | 3.889377 | 31.305886 | 27.484441 | 21.737770 | 4.939860 | 4.193983 | -2.529562 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 182 | N13 | RF_maintenance | nn Power | 29.496350 | 17.393825 | 3.286780 | 29.496350 | 26.151865 | 28.421879 | 7.778157 | 1.446354 | -1.048543 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 182 | N13 | RF_maintenance | nn Power | 41.047376 | 19.961318 | 6.067371 | 41.047376 | 36.028998 | 16.470240 | 3.632353 | 2.019811 | -1.321810 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 182 | N13 | RF_maintenance | ee Power | 171.537879 | 41.298317 | 14.889959 | 171.537879 | 6.655057 | 91.163273 | 4.623611 | -2.445624 | 12.817141 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 182 | N13 | RF_maintenance | nn Temporal Variability | 71.007687 | 19.941698 | 6.396738 | 20.305090 | 16.479589 | 71.007687 | 69.240909 | 2.601149 | -2.747641 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 182 | N13 | RF_maintenance | nn Shape | 13.669732 | 0.562101 | 13.669732 | -0.885641 | 9.914313 | -2.683787 | -0.565022 | -1.602318 | 1.497989 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 182 | N13 | RF_maintenance | ee Temporal Variability | 123.396389 | 39.517404 | 15.215610 | 108.411565 | 4.592166 | 123.396389 | 8.225369 | 0.423623 | 8.847037 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 182 | N13 | RF_maintenance | ee Temporal Discontinuties | 11.535360 | -0.335713 | -0.483160 | -1.200311 | -1.234349 | 0.625387 | 3.168218 | 7.750606 | 11.535360 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 182 | N13 | RF_maintenance | nn Temporal Variability | 28.599642 | 20.880372 | 4.246101 | 23.549325 | 19.636755 | 28.599642 | 7.799046 | 2.304017 | -2.616841 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 182 | N13 | RF_maintenance | nn Temporal Discontinuties | 72.737726 | 4.954974 | 4.922677 | 0.705760 | 11.826375 | 69.797707 | 13.980431 | 72.737726 | -6.498965 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 182 | N13 | RF_maintenance | nn Temporal Variability | 256.239672 | 16.255146 | 15.780982 | 7.294666 | 51.038025 | 256.239672 | 113.751834 | 146.009039 | -0.754341 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 182 | N13 | RF_maintenance | nn Temporal Discontinuties | 21.452844 | 11.108815 | 8.303147 | 16.172813 | 14.614133 | 8.018944 | 0.176445 | -1.288315 | 21.452844 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 182 | N13 | RF_maintenance | ee Temporal Discontinuties | 6.690637 | -0.174527 | -0.315835 | -1.036342 | -1.123362 | 3.367159 | 2.358612 | 6.690637 | 5.906790 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 182 | N13 | RF_maintenance | nn Temporal Discontinuties | 40.986779 | 12.656442 | 7.717757 | 21.461123 | 21.041305 | 25.592522 | 5.401337 | -3.810343 | 40.986779 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 182 | N13 | RF_maintenance | nn Temporal Discontinuties | 62.718553 | 11.121478 | 9.732104 | 19.006246 | 21.218625 | 6.986638 | 16.754160 | 62.718553 | -5.444980 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 182 | N13 | RF_maintenance | nn Temporal Discontinuties | 219.170447 | 5.858220 | 11.438031 | 17.982697 | 16.299139 | 125.565569 | 25.060113 | 219.170447 | -3.737757 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 182 | N13 | RF_maintenance | nn Temporal Variability | 118.801985 | 8.050530 | 7.483698 | 26.739471 | 17.042145 | 14.881995 | 118.801985 | -1.551207 | 1.147623 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 182 | N13 | RF_maintenance | nn Power | 36.067249 | 18.412693 | 11.438567 | 36.067249 | 22.020084 | 33.218514 | 33.308063 | 11.530607 | -1.718336 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 182 | N13 | RF_maintenance | ee Temporal Variability | 18.667460 | 2.553797 | 11.996922 | 7.642397 | 16.956193 | 3.760572 | 18.667460 | 4.617942 | -0.877808 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 182 | N13 | RF_maintenance | nn Temporal Discontinuties | 36.311558 | 5.784974 | 1.666256 | 23.274730 | 7.098508 | 4.125275 | 7.511980 | -2.327407 | 36.311558 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 182 | N13 | RF_maintenance | nn Power | 47.253742 | 26.135180 | 15.421866 | 47.253742 | 18.755413 | 33.503137 | 24.220842 | 30.632902 | 10.591726 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 182 | N13 | RF_maintenance | nn Power | 43.474758 | 13.963081 | 27.434809 | 20.554135 | 43.474758 | 21.769330 | 27.984314 | -0.644091 | 0.967505 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 182 | N13 | RF_maintenance | nn Temporal Variability | 134.855845 | 6.965426 | 15.752882 | 5.563514 | 20.320151 | 134.855845 | 18.180795 | 5.069013 | -1.699521 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 182 | N13 | RF_maintenance | ee Temporal Variability | 43.189761 | 9.829794 | 15.556082 | 24.174927 | 31.286431 | 43.189761 | 19.395903 | -2.730088 | 40.627750 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 182 | N13 | RF_maintenance | nn Temporal Variability | 81.386069 | 15.682966 | 3.189414 | 16.826495 | 22.675547 | 25.854713 | 81.386069 | -0.379603 | 12.062639 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 182 | N13 | RF_maintenance | nn Power | 42.743077 | 19.580018 | 10.207241 | 42.743077 | 24.404789 | 39.422087 | 33.911830 | 8.226924 | -4.549940 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 182 | N13 | RF_maintenance | nn Power | 45.458950 | 21.257362 | 14.701544 | 45.458950 | 19.086652 | 39.355068 | 33.629448 | 10.472590 | 2.277924 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 182 | N13 | RF_maintenance | nn Shape | nan | nan | nan | nan | nan | nan | nan | nan | nan |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 182 | N13 | RF_maintenance | nn Shape | nan | nan | nan | inf | inf | nan | nan | nan | nan |